package com.hkbigdata.window;

import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.KeyedStream;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.util.Collector;

/**
 * @author liuanbo
 * @creat 2023-04-23-15:49
 * @see 2194550857@qq.com
 */
public class Flink04_Window_CountSlide {
    public static void main(String[] args) throws Exception {
        //1.获取执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);

        //2.读取端口数据
        DataStreamSource<String> socketTextStream = env.socketTextStream("hadoop102", 9999);

        //3.压平并转换为元组
        SingleOutputStreamOperator<Tuple2<String, Integer>> wordToOneDS = socketTextStream.flatMap(new FlatMapFunction<String, Tuple2<String, Integer>>() {
            @Override
            public void flatMap(String value, Collector<Tuple2<String, Integer>> out) throws Exception {
                String[] words = value.split(" ");
                for (String word : words) {
                    out.collect(new Tuple2<>(word, 1));
                }
            }
        });

        KeyedStream<Tuple2<String, Integer>, String> keyedStream = wordToOneDS.keyBy(data -> data.f0);

        keyedStream.countWindow(5L,2L).sum(1).print();

        env.execute();

    }
}
